https://github.com/curtinids/r-novice-gapminder
Introduction to R for non-programmers using gapminder data.
Science Score: 18.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (7.2%) to scientific vocabulary
Repository
Introduction to R for non-programmers using gapminder data.
Basic Info
- Host: GitHub
- Owner: CurtinIDS
- License: other
- Language: Python
- Default Branch: gh-pages
- Homepage: http://swcarpentry.github.io/r-novice-gapminder/
- Size: 24.1 MB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
R for Reproducible Scientific Analysis
An introduction to R for non-programmers using the Gapminder data.
Please see https://swcarpentry.github.io/r-novice-gapminder for a rendered version of this material,
the lesson template documentation
for instructions on formatting, building, and submitting material,
or run make in this directory for a list of helpful commands.
The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.
Note that this workshop focuses on the fundamentals of the programming language R, and not on statistical analysis.
A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.
Maintainers:
Owner
- Name: Curtin Institute for Data Science
- Login: CurtinIDS
- Kind: organization
- Email: curtinids@curtin.edu.au
- Location: Perth, Australia
- Website: http://computation.curtin.edu.au
- Repositories: 1
- Profile: https://github.com/CurtinIDS
Meeting the increasing demand for computational tools in research
Citation (CITATION)
Please cite as: Thomas Wright and Naupaka Zimmerman (eds): "Software Carpentry: R for Reproducible Scientific Analysis." Version 2016.06, June 2016, https://github.com/swcarpentry/r-novice-gapminder, 10.5281/zenodo.57520.